1. Field of the Invention
The present invention relates to an unwanted signal suppression device using a filter such as a clutter suppression device for eliminating reflection echoes caused by clutter or the like of signals, except for signals of interest, which have been received by a plurality of lattice type filters (hereafter called lattice filter) connected in cascade, for example, in a pulse radar, and a clutter suppression device to cause the notch of a notch filter for removing reflection echoes by clutter or the like to adaptively follow the reflection echoes.
2. Description of the Prior Art
An example of the clutter suppression device for removing unwanted signals except for reflection echoes from the target signals such as clutter or the like which are received by a pulse radar is known, for example, from the article by Hideaki Watanabe et al. titled "Adaptive Clutter Suppression Device by Use of a Plurality of Segments MEM" published in the Proceedings of Electronic Information Communication Society, Vol. J70-B No. 4, pp. 515-523 (April 1987).
FIG. 1 is a block diagram of a circuit illustrating a constitution of a clutter suppression device according to a prior art. In FIG. 1, reference numerals 1a and 1b designate reflection coefficient computing means, reference numerals 2a and 2b delay elements, reference numerals 3a, 3b, 3c and 3d complex multipliers and reference numerals 4a, 4b, 4c and 4d complex adders. Symbols X(n), f.sup.m (n), b.sup.m (n), P.sub.m (n=1-3, m=1, 2) represent respectively the vector of the signals which are respectively expressed in the following equations. P.sub.m (m=1, 2) is reflection coefficient. EQU X(n)=[X.sub.1 (n),X.sub.2 (n), . . . , X.sub.k (n)].sup.T ( 1a) EQU f.sup.m (n)=[f.sub.1.sup.m (n), f.sub.2.sup.m (n), . . . , f.sub.k.sup.m (n)].sup.T ( 1b) EQU b.sup.m (n)=[b.sub.1.sup.m (n),b.sub.2.sup.m (n), . . . ,b.sub.k.sup.m (n)].sup.T ( 1c) EQU P.sub.m =diag[.rho..sub.1.sup.m,.rho..sub.2.sup.m, . . . ,.rho..sub.k.sup.m ] (1d)
where T designates a transpose and diag [ ] designates the diagonal matrix.
Next are explained the definition of the suffix m, suffix k, suffix n and the respective signals which are used in the above notation of signals by referring to FIG. 2.
FIG. 2 is a diagram illustrating the timing relationship among the signals transmitted and received by the pulse radar, wherein reference numerals 5a, 5b and 5c designate the pulses of the transmission signals and reference numerals 6a, 6b and 6c designate the reception signals. The pulse radar generates therein a plurality of pulse electric waves having a pulse width of .tau. and emits these pulse electric waves to an external space in a constant pulse repetition period of T as transmission signals. The transmission signals are numbered in the sequential order of their emission to the outside. In FIG. 2, reference numeral 5a designates the first transmission signal, reference numeral 5b the second transmission signal and reference numeral 5c the n-th transmission signal.
The pulse radar receives a series of reception electric waves during the interval between transmissions of the pulse electric waves and converts them into electrical signals by means of the receiver installed therein and takes in these electrical signals as reception signals. These reception signals are also numbered in a similar manner to the case of said transmission signals and those numbers are referred to as pulse hit numbers. In FIG. 2, reference numeral 6a designates the first reception signal, reference numeral 6b the second reception signal and reference numeral 6c the n-th reception signal.
The pulse radar is adapted, after having executed phase detection of a series of reception electric waves and converting them into reception signals of base bands, to convert such reception signals into digital signals by sampling and quantitizing them. These digital signals retain the phase of the reception electric waves and are complex signals having the so-called I signal (in-phase) and Q signal (quadrature-phase) respectively at the real part and the imaginary part. Sampling of the signals is executed by use of the same timing for all of the reception signals as illustrated in FIG. 2. More specifically, after a delay of the time .tau..sub.d from the time of transmission of the transmission signals, sampling is executed in a constant cycle .tau..sub.s and the total number k of digital signals as expressed by X.sub.1 (n), X.sub.2 (n), . . . , X.sub.k (n) are generated from one reception signal as shown in FIG. 2. It is to be noted here that n designates the pulse hit number and k designates the sequential order of sampling. K is called a range bin number.
The digital signals X(n) which have been obtained by the pulse radar as above explained are subsequently transferred as the input signals for the clutter suppression device and are referred to as input signals hereinbelow.
The suffix m represents stage numbers of the lattice filter as shown in FIG. 1.
Operation of a conventional device will next be explained by referring to FIG. 1. The input signal vector X(n) (n=1-3) transferred from the pulse radar is input to the lattice filter at the stage 1. At this time, the input signal X(n) is used as a forward prediction error signal vector f.sup.o (n) and a backward prediction error signal vector b.sup.o (n) as expressed in the equations 2a and 2b. EQU f.sup.o (n)=X(n) (2a) EQU b.sup.o (n)=X(n) (2b)
The lattice filter at the stage 1 generates signal vectors f.sup.1 (n) and b.sup.1 (n) from the signal vectors f.sup.o (n) and b.sup.o (n) in accordance with the equations 3a and 3b. EQU f.sup.1 (n)=f.sup.o (n)+P.sub.1 b.sub.o (n-1) (3a) EQU b.sup.1 (n)=b.sup.o (n-1)+P.sub.1* f.sub.o (n) (3b)
where n=2, 3 and * stands for complex conjugate.
In operation of the equations 3a and 3b, multiplication is executed by the complex multipliers 3a and 3b, addition is executed by the complex adders 4a and 4b and unit delay with respect to backward prediction signal vector b.sup.o (n) is executed by the delay element 2a.
At the same time, the reflection coefficient computing means 1a receives the vector f.sup.o (n) and the vector b.sup.o (n) to compute reflection coefficient .rho..sub.1. Since the clutter suppression device according to a prior art will not suppress the target signals, when the i-th range bin is processed, a plurality of range bins equivalent to the number of NL and NR displaced respectively by .DELTA.R from the i-th range excluding the i-th range bin are selected and used as the data for computing the reflection coefficient as illustrated in FIG. 3. This operation is executed under the assumption that the target signal is present only for one range bin while the clutter is present in a very wide range and that the power spectrum of the clutter will not suddenly change in its range.
The reflection coefficient vector P.sub.1 is generated based on the following equations (4a) through (5b). ##EQU1## where k: total number of range bins
i: processing range bin number PA0 NL: size of the data for computing reflection coefficient at the left side of the processing range bin PA0 NR: size of the data for computing reflection coefficient at the right side of the processing range bin PA0 .DELTA.R: number of interval range bins between the processing range bin and the data for computing the reflection coefficient. PA0 where n=3.
The algorithm for computing the reflection coefficient as expressed in the equation 5a is an application of the known Burg method and is the algorithm for minimizing the sum of square power of the forward prediction error signal vector f.sup.1 (n) and the backward prediction error signal vector b.sup.1 (n).
Then, the lattice filter at the stage 2 receives the prediction error signal vector f.sup.1 (n) and b.sup.1 (n) to generate signal vectors f.sup.2 (n) and b.sup.2 (n) based on the following equations 6a and 6b. EQU f.sup.2 (n)=f.sup.1 (n)+P.sub.2 .multidot.b.sup.1 (n-1) (6a) EQU b.sup.2 (n)=b.sup.1 (n-1)+P.sub.2 *.multidot.f.sup.1 (n) (6b)
In operation of the equations 6a and 6b, multiplication is executed by the complex multipliers 3c and 3d, addition is executed by the complex adders 4c and 4d, and unit delay applied to the signal vector b.sup.1 (n) is executed by the delay element 2b.
Concurrently with this operation, the reflection coefficient computing means 1b receives the vectors f.sup.1 (n) and b.sup.1 (n) to generate the reflection coefficient vector P.sub.2 necessary for the equations 6a and 6b in accordance with the following equations 7a through 8b. ##EQU2##
The algorithm for computing the reflection coefficient P.sub.2 as expressed by the equation 8a and 8b is based on that of Burg method in the same manner as the equations 5a and 5b.
Lastly, the forward prediction error signal vector f.sup.2 (3) at the stage 2 is taken out to the outside as an output signal from the clutter suppression device.
As explained above, the conventional clutter suppression device was intended to eliminate the clutter contained in the input signals by sequentially generating the forward prediction error signals and the backward prediction error signals from the input signals X(n) (provided n=1-3) and minimizing the square mean power of the output signals. This is equivalent to elimination of the intense spectrum component out of the Doppler spectrum contained in the input signal vectors X(1), X(2) and X(3). Under a normal electric wave environment, the more intense spectrum component(s) in the input signal is (are) the clutter spectrum. Thus, the clutter may be suppressed. In a circumstance wherein a large target is present at a rather short distance, the target signal power may be far larger than the clutter power. However, since the processing range bin i and the range bins including the data for computing the reflection coefficient (i.e., the range bins in the sizes NL and NR) are separated with each other, the target signals will not be suppressed.
FIGS. 4(a) and 4(b) illustrate the manner in which the clutter signals are suppressed. FIG. 4(a) illustrates a condition in which the clutter is present in a very wide range and the target signal exists in the processing range bin i, while FIG. 4(b) illustrates that the filter transfer function is generated in the above-mentioned condition so that the clutter spectrum 24 will be suppressed. In FIG. 4(b), reference numeral 23 designates a filter transfer function generated by the filter, reference numeral 23a a notch which is the suppressing part of the filter transfer function 23, reference numeral 24 the clutter spectrum, reference numeral 25 the target signal spectrum, reference numeral 27 null formed by the notch 23a, reference character W the width of the notch 23a, reference character D the depth of the notch 23a, reference character N the notch frequency of the notch 23a, and reference character X the range in which the clutter spectrum 24 has been suppressed by the null 27.
Thus, the null of the filter is caused by the range X to suppress the clutter. Namely, the reflection coefficient for the processing range bin i in which the target signal is present is computed by the data of the range bins inside NL and NR or the data of the clutter signal, such that the clutter may be suppressed.
Reference is next made to FIGS. 5(a) and 5(b) which illustrate the condition in which the target signal is present along with the clutter signals outside the processing range bin. FIG. 5(a) illustrates the condition in which the clutter signals are present in wide range bins while the target signal is present in the range bin i-3 included in NL. In this condition, since the target signal is included in NL, when the reflection coefficient of the processing range bin i is computed, null of the filter is generated for the frequency of the target signal as shown in FIG. 5(b), such that the clutter spectrum 24 will not be suppressed.
As shown in FIG. 3, since the conventional clutter suppression device separates the processing range bin i from the range bins (i.e., the range bins within NL and NR) having the data for computing the reflection coefficient for said processing bin, when a target signal of a large power is received, and if the range bins in which the target signal is present are to be processed, the null of the filter is generated for the clutter as shown in FIG. 4(b). However, in case of such a range as a target signal is included within the range bins (i.e., the range within NL and NR) having the data for use of computing the reflection coefficient shown in FIG. 3, the null is generated for the Doppler frequency of the target signal as shown in FIG. 5(b), resulting in an inability to suppress the clutter.
Furthermore, according to the conventional clutter suppression device, since the notch frequency N and the depth D of the notch of the filter for suppressing the clutter had to be controlled simultaneously, a sufficient number of data samples are required for converging a filter weight to an optimum value. Accordingly in such a radar system as a search radar in which only a few pulse bits obtained, the filter weight cannot be adequately converged, so that the notch frequency or the notch depth may be subject to variation resulting in incomplete clutter suppression.